Problem Statement: The spectator/bystander of any accident in India is currently limited by various constraints despite his sincere willingness to help in the circumstance. Current system has a telephone redressal system with a dedicated phone number which redirects the caller (here bystander/spectator) to a call center. The receiver at the call center gathers the mandatory basic information from the caller and dispatches appropriate services. The basic information obtained includes the location of the incident (exact location/landmark), type of emergency, number of people injured and the condition of the injured, the caller's name and contact number (for location guidance if required).
What if the caller, who wants to help, doesn’t know the location of the accident? What if he has to move on for some emergency reasons and may not be able co-operate for location guidance? What if the person from call center forgets to ask a few important questions such as the type of emergency? Being humans, there is every possible chance of us making an error. But the stakes are too high to commit an error. Any feasible solution that can minimize this error at least by a few margin is worth considering.
Objective: * To maximise the role of the bystander (third person/party) with his minimal effort in helping the victims of an accident using technology. * To construct a fool proof mechanism to minimize the pranks and also to categorize the accidents based on the severity.
The idea is to develop a user friendly mobile application which can be integrated with existing system in place. The app after capturing images and getting necessary information from the user attaches location and time stamps to the data using built-in features of mobile phones and sends them to a database. From here, it functions the same as that of a telephone redressal system wherein ambulances nearest to the location are notified.
Features that we want to build: * To capture images only via the app to send them to the database. * To attach location and time stamps along with the images. * Information on the emergency of the situation by user prompt.
Features that are good to have: * Auto focus and auto Image capture feature for user convenience. * A developed machine learning algorithm to categorise images in terms of severity of the emergency after getting uploaded to the database.
Constraints: * Limited by the number of smart phone users around the incident. * Lack of proper internet connectivity at the location of the incident for a bystander.
Known issues: * Fake images can be uploaded using the app. Hence it is mandated to take the images from the app. * The bystander as well as images uploaded cannot give the complete information related to the incident (Examples: Severity of the accident if a person is met with an internal injury or fracture, when did the accident take place and the like)
9Apps 4.9
